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Sensors fault diagnosis of hydraulic automatic gauge control system based on neural network optimized by genetic algorithm

机译:基于神经网络优化遗传算法的液压自动规测控系统的传感器故障诊断

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According to the shortcomings of slower convergence speed and easy to fall into the local optimal of BP neural network, a method that weights and thresholds of BP neural network are optimized by genetic algorithm which has the global search ability is put forward, using the optimized BP network by genetic algorithm, the simulation experiments are conducted using a lot of sensor data of modern strip mill hydraulic automatic gauge control system, experiments show that this algorithm has obvious superiority, the shortages of BP algorithm are avoided, the learning performances of network are improved greatly, and it has certain practicability.
机译:根据较慢的收敛速度且易于落入本地最佳的BP神经网络的缺点,通过优化的BP提出了BP神经网络的重量和阈值的方法,该方法通过了全球搜索能力,优化的BP通过遗传算法进行仿真实验,使用大量传感器数据进行现代条带液压自动规格控制系统,实验表明,该算法具有明显的优势,避免了BP算法的短缺,提高了网络的学习性能大大,它具有一定的实用性。

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